Move all decorators in the scene subfolder

cura/Arranging/Arrange.py

@@ -1,8 +1,8 @@
 from UM.Scene.Iterator.DepthFirstIterator import DepthFirstIterator
 from UM.Logger import Logger
 from UM.Math.Vector import Vector
-from cura.ShapeArray import ShapeArray
-from cura import ZOffsetDecorator
+from cura.Arranging.ShapeArray import ShapeArray
+from cura.Scene import ZOffsetDecorator
 
 from collections import namedtuple
 

cura/Arranging/ArrangeObjectsAllBuildPlatesJob.py

@@ -10,9 +10,9 @@ from UM.Message import Message
 from UM.i18n import i18nCatalog
 i18n_catalog = i18nCatalog("cura")
 
-from cura.ZOffsetDecorator import ZOffsetDecorator
+from cura.Scene.ZOffsetDecorator import ZOffsetDecorator
 from cura.Arranging.Arrange import Arrange
-from cura.ShapeArray import ShapeArray
+from cura.Arranging.ShapeArray import ShapeArray
 
 from typing import List
 

cura/Arranging/ArrangeObjectsJob.py

@@ -11,9 +11,9 @@ from UM.Message import Message
 from UM.i18n import i18nCatalog
 i18n_catalog = i18nCatalog("cura")
 
-from cura.ZOffsetDecorator import ZOffsetDecorator
+from cura.Scene.ZOffsetDecorator import ZOffsetDecorator
 from cura.Arranging.Arrange import Arrange
-from cura.ShapeArray import ShapeArray
+from cura.Arranging.ShapeArray import ShapeArray
 
 from typing import List
 

cura/Arranging/ShapeArray.py

@@ -0,0 +1,116 @@
+import numpy
+import copy
+
+from UM.Math.Polygon import Polygon
+
+
+##  Polygon representation as an array for use with Arrange
+class ShapeArray:
+    def __init__(self, arr, offset_x, offset_y, scale = 1):
+        self.arr = arr
+        self.offset_x = offset_x
+        self.offset_y = offset_y
+        self.scale = scale
+
+    ##  Instantiate from a bunch of vertices
+    #   \param vertices
+    #   \param scale  scale the coordinates
+    @classmethod
+    def fromPolygon(cls, vertices, scale = 1):
+        # scale
+        vertices = vertices * scale
+        # flip y, x -> x, y
+        flip_vertices = numpy.zeros((vertices.shape))
+        flip_vertices[:, 0] = vertices[:, 1]
+        flip_vertices[:, 1] = vertices[:, 0]
+        flip_vertices = flip_vertices[::-1]
+        # offset, we want that all coordinates have positive values
+        offset_y = int(numpy.amin(flip_vertices[:, 0]))
+        offset_x = int(numpy.amin(flip_vertices[:, 1]))
+        flip_vertices[:, 0] = numpy.add(flip_vertices[:, 0], -offset_y)
+        flip_vertices[:, 1] = numpy.add(flip_vertices[:, 1], -offset_x)
+        shape = [int(numpy.amax(flip_vertices[:, 0])), int(numpy.amax(flip_vertices[:, 1]))]
+        arr = cls.arrayFromPolygon(shape, flip_vertices)
+        return cls(arr, offset_x, offset_y)
+
+    ##  Instantiate an offset and hull ShapeArray from a scene node.
+    #   \param node source node where the convex hull must be present
+    #   \param min_offset offset for the offset ShapeArray
+    #   \param scale scale the coordinates
+    @classmethod
+    def fromNode(cls, node, min_offset, scale = 0.5):
+        transform = node._transformation
+        transform_x = transform._data[0][3]
+        transform_y = transform._data[2][3]
+        hull_verts = node.callDecoration("getConvexHull")
+        # If a model is too small then it will not contain any points
+        if hull_verts is None or not hull_verts.getPoints().any():
+            return None, None
+        # For one_at_a_time printing you need the convex hull head.
+        hull_head_verts = node.callDecoration("getConvexHullHead") or hull_verts
+
+        offset_verts = hull_head_verts.getMinkowskiHull(Polygon.approximatedCircle(min_offset))
+        offset_points = copy.deepcopy(offset_verts._points)  # x, y
+        offset_points[:, 0] = numpy.add(offset_points[:, 0], -transform_x)
+        offset_points[:, 1] = numpy.add(offset_points[:, 1], -transform_y)
+        offset_shape_arr = ShapeArray.fromPolygon(offset_points, scale = scale)
+
+        hull_points = copy.deepcopy(hull_verts._points)
+        hull_points[:, 0] = numpy.add(hull_points[:, 0], -transform_x)
+        hull_points[:, 1] = numpy.add(hull_points[:, 1], -transform_y)
+        hull_shape_arr = ShapeArray.fromPolygon(hull_points, scale = scale)  # x, y
+
+        return offset_shape_arr, hull_shape_arr
+
+    ##  Create np.array with dimensions defined by shape
+    #   Fills polygon defined by vertices with ones, all other values zero
+    #   Only works correctly for convex hull vertices
+    #   Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
+    #   \param shape  numpy format shape, [x-size, y-size]
+    #   \param vertices
+    @classmethod
+    def arrayFromPolygon(cls, shape, vertices):
+        base_array = numpy.zeros(shape, dtype=float)  # Initialize your array of zeros
+
+        fill = numpy.ones(base_array.shape) * True  # Initialize boolean array defining shape fill
+
+        # Create check array for each edge segment, combine into fill array
+        for k in range(vertices.shape[0]):
+            fill = numpy.all([fill, cls._check(vertices[k - 1], vertices[k], base_array)], axis=0)
+
+        # Set all values inside polygon to one
+        base_array[fill] = 1
+
+        return base_array
+
+    ##  Return indices that mark one side of the line, used by arrayFromPolygon
+    #   Uses the line defined by p1 and p2 to check array of
+    #   input indices against interpolated value
+    #   Returns boolean array, with True inside and False outside of shape
+    #   Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
+    #   \param p1 2-tuple with x, y for point 1
+    #   \param p2 2-tuple with x, y for point 2
+    #   \param base_array boolean array to project the line on
+    @classmethod
+    def _check(cls, p1, p2, base_array):
+        if p1[0] == p2[0] and p1[1] == p2[1]:
+            return
+        idxs = numpy.indices(base_array.shape)  # Create 3D array of indices
+
+        p1 = p1.astype(float)
+        p2 = p2.astype(float)
+
+        if p2[0] == p1[0]:
+            sign = numpy.sign(p2[1] - p1[1])
+            return idxs[1] * sign
+
+        if p2[1] == p1[1]:
+            sign = numpy.sign(p2[0] - p1[0])
+            return idxs[1] * sign
+
+        # Calculate max column idx for each row idx based on interpolated line between two points
+
+        max_col_idx = (idxs[0] - p1[0]) / (p2[0] - p1[0]) * (p2[1] - p1[1]) + p1[1]
+        sign = numpy.sign(p2[0] - p1[0])
+        return idxs[1] * sign <= max_col_idx * sign
+